Hi, it’s a number based on simulations. I didn’t want to talk about statistical power, but if a study has 80% power (the traditional definition of “adequate sample size” in psychology/neuroscience), then 26% of significant p-values will be .01 < p < .05, i.e., #(.01 < p < .05) / #(p < .05)
This graph shows the relationship between statistical power and the percentage of p-values that will be .01 < p < .05: https://imgur.com/086tHUT
Hi, it’s a number based on simulations. I didn’t want to talk about statistical power, but if a study has 80% power (the traditional definition of “adequate sample size” in psychology/neuroscience), then 26% of significant p-values will be .01 < p < .05, i.e., #(.01 < p < .05) / #(p < .05)
This graph shows the relationship between statistical power and the percentage of p-values that will be .01 < p < .05: https://imgur.com/086tHUT
You can find some rates from actual studies in Figure 2 here: https://journals.sagepub.com/doi/pdf/10.1177/25152459251323480#page=6